The Community for Technology Leaders
RSS Icon
Issue No.06 - November/December (2011 vol.8)
pp: 1495-1508
Murat Can Cobanoglu , Sabanci University, Istanbul
Yucel Saygin , Sabanci University, Istanbul
Ugur Sezerman , Sabanci University, Istanbul
The classification of G-Protein Coupled Receptor (GPCR) sequences is an important problem that arises from the need to close the gap between the large number of orphan receptors and the relatively small number of annotated receptors. Equally important is the characterization of GPCR Class A subfamilies and gaining insight into the ligand interaction since GPCR Class A encompasses a very large number of drug-targeted receptors. In this work, we propose a method for Class A subfamily classification using sequence-derived motifs which characterizes the subfamilies by discovering receptor-ligand interaction sites. The motifs that best characterize a subfamily are selected by the Distinguishing Power Evaluation (DPE) technique we propose. The experiments performed on GPCR sequence databases show that our method outperforms state-of-the-art classification techniques for GPCR Class A subfamily prediction. An important contribution of our work is to discover key receptor-ligand interaction sites which is very important for drug design.
Sequence analysis, GPCR classification, data mining, motif selection.
Murat Can Cobanoglu, Yucel Saygin, Ugur Sezerman, "Classification of GPCRs Using Family Specific Motifs", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.8, no. 6, pp. 1495-1508, November/December 2011, doi:10.1109/TCBB.2010.101
[1] T. Kenakin, “Allosteric Modulators: The New Generation of Receptor Antagonist,” Molecular Interventions, vol. 4, no. 4, pp. 222-229, 2004.
[2] T.E. Hebert and M. Bouvier, “Structural and Functional Aspects of G Protein-Coupled Receptor Oligomerization,” Biochemistry and Cell Biology, vol. 76, no. 1, pp. 1-11, 1998.
[3] D. Filmore, “It's a GPCR World,” Modern Drug Discovery, vol. 7, no. 11, pp. 24-28, Nov. 2004.
[4] Y. Zhang, M.E. DeVries, and J. Skolnick, “Structure Modeling of All Identified G Protein-Coupled Receptors in the Human Genome,” PLoS Computational Biology, vol. 2, no. 2, p. e13, Feb. 2006.
[5] B. Erguner, O. Erdogan, and U. Sezerman, “Prediction and Classification for GPCR Sequences Based on Ligand Specific Features,” Proc. Int'l Symp. Computer and Information Sciences (ISCIS '06), pp. 174-181, 2006.
[6] M.N. Davies, A. Secker, A.A. Freitas, E. Clark, J. Timmis, and D.R. Flower, “Optimizing Amino Acid Groupings for GPCR Classification,” Bioinformatics, vol. 24, no. 18, pp. 1980-1986, Sept. 2008.
[7] J. Cui, L.Y. Han, H. Li, C.Y. Ung, Z.Q. Tang, C.J. Zheng, Z.W. Cao, and Y.Z. Chen, “Computer Prediction of Allergen Proteins from Sequence-Derived Protein Structural and Physicochemical Properties,” Molecular Immunology, vol. 44, no. 4, pp. 514-520, Jan. 2007.
[8] M.N. Davies, A. Secker, A.A. Freitas, M. Mendao, J. Timmis, and D.R. Flower, “On the Hierarchical Classification of G Protein-Coupled Receptors,” Bioinformatics, vol. 23, no. 23, pp. 3113-3118, Dec. 2007.
[9] M.N. Davies, A. Secker, M. Halling-Brown, D.S. Moss, A.A. Freitas, J. Timmis, E. Clark, and D.R. Flower, “Gpcrtree: Online Hierarchical Classification of Gpcr Function,” BMC Research Notes, vol. 1, p. 67, 2008.
[10] B. Bakir and U. Sezerman, “Functional Classification of G-Protein Coupled Receptors, Based on Their Specific Ligand Coupling Patterns,” Lecture Notes in Computer Science, Franz Rothlauf et al. (eds.), vol. 3907, pp. 1-12, Springer, 2006.
[11] R. Karchin, K. Karplus, and D. Haussler, “Classifying G-Protein Coupled Receptors with Support Vector Machines,” Bioinformatics, vol. 18, no. 1, pp. 147-159, Jan. 2002.
[12] Y. Yabuki, T. Muramatsu, T. Hirokawa, H. Mukai, and M. Suwa, “Griffin: A System for Predicting Gpcr-G-Protein Coupling Selectivity Using a Support Vector Machine and a Hidden Markov Model,” Nucleic Acids Research, vol. 33 (suppl. 2), pp. W148-W153, July 2005.
[13] W.R. Atchley, J. Zhao, A.D. Fernandes, and T. Drüke, “Solving the Protein Sequence Metric Problem,” Proc. Nat'l Academy of Sciences USA, vol. 102, no. 18, pp. 6395-6400, May 2005.
[14] F. Horn, J. Weare, M.W. Beukers, S. Horsch, A. Bairoch, W. Chen, O. Edvardsen, F. Campagne, and G. Vriend, “Gpcrdb: An Information System for G Protein-Coupled Receptors,” Nucleic Acids Research, vol. 26, no. 1, pp. 275-279, Jan. 1998.
[15] G. Salton, “Developments in Automatic Text Retrieval,” Science, vol. 253, no. 5023, pp. 974-980, Aug. 1991.
[16] J.R. Quinlan, “Induction of Decision Trees,” Machine Learning, vol. 1, no. 1, pp. 81-106, Mar. 1986.
[17] J.R. Quinlan, “Simplifying Decision Trees,” Int'l J. Man-Machine Studies, vol. 27, no. 3, pp. 221-234, 1987.
[18] Y. Freund and R. Schapire, “A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting,” Proc. Conf. Computational Learning Theory, pp. 23-37, 1995.
[19] U. Gether, “Uncovering Molecular Mechanisms Involved in Activation of G Protein-Coupled Receptors,” Endocrine Rev., vol. 21, no. 1, pp. 90-113, 2000.
[20] D.M. Rosenbaum, S.G.F. Rasmussen, and B.K. Kobilka, “The Structure and Function of G-Protein-Coupled Receptors,” Nature, vol. 459, no. 7245, pp. 356-363, May 2009.
[21] P.J. Conn, A. Christopoulos, and C.W. Lindsley, “Allosteric Modulators of GPCRs: A Novel Approach for the Treatment of CNS Disorders,” Nature Rev. Drug Discovery, vol. 8, no. 1, pp. 41-54, Jan. 2009.
[22] S.M. Foord, T.I. Bonner, R.R. Neubig, E.M. Rosser, J.P. Pin, A.P. Davenport, M. Spedding, and A.J. Harmar, “International Union of Pharmacology. XLVI. G Protein-Coupled Receptor List,” Pharmacological Rev., vol. 57, no. 2, pp. 279-288, 2005.
[23] P. Joost and A. Methner, “Phylogenetic Analysis of 277 Human G-Protein-Coupled Receptors as a Tool for the Prediction of Orphan Receptor Ligands,” Genome Biology, vol. 3, no. 11, pp. 1-16, 2002.
[24] F. Libert, M. Parmentier, A. Lefort, C. Dinsart, J. Van Sande, C. Maenhaut, M.J. Simons, J.E. Dumont, and G. Vassart, “Selective Amplification and Cloning of Four New Members of the G Protein-Coupled Receptor Family,” Science, vol. 244, no. 4904, pp. 569-572, 1989.
[25] A. Methner, G. Hermey, B. Schinke, and I. Hermans-Borgmeyer, “A Novel G Protein-Coupled Receptor with Homology to Neuropeptide and Chemoattractant Receptors Expressed during Bone Development,” Biochemical and Biophysical Research Comm., vol. 233, no. 2, pp. 336-342, Apr. 1997.
[26] A. Krogh, B. Larsson, G. von Heijne, and E.L.L. Sonnhammer, “Predicting Transmembrane Protein Topology with a Hidden Markov Model: Application to Complete Genomes,” J. Molecular Biology, vol. 305, no. 3, pp. 567-580, Jan. 2001.
[27] S. Möller, M.D. Croning, and R. Apweiler, “Evaluation of Methods for the Prediction of Membrane Spanning Regions,” Bioinformatics, vol. 17, no. 7, pp. 646-653, July 2001.
[28] M. Bhasin and G.P. Raghava, “GPCRpred: An Svm-Based Method for Prediction of Families and Subfamilies of G-Protein Coupled Receptors,” Nucleic Acids Research, vol. 32, pp. W383-W389, July 2004.
[29] P.K. Papasaikas, P.G. Bagos, Z.I. Litou, V.J. Promponas, and S.J. Hamodrakas, “PRED-GPCR: GPCR Recognition and Family Classification Server,” Nucleic Acids Research, vol. 32, pp. W380-W382, 2004.
19 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool